Characterizing Fractal Genetic Variation in the Human Genome from the Hapmap Project

Over the last decades, the exuberant development of next-generation sequencing has revolutionized gene discovery. These technologies have boosted the mapping of single nucleotide polymorphisms (SNPs) across the human genome, providing a complex universe of heterogeneity characterizing individuals worldwide. Fractal dimension (FD) measures the degree of geometric irregularity, quantifying how "complex" a self-similar natural phenomenon is. We compared two FD algorithms, box-counting dimension (BCD) and Higuchi's fractal dimension (HFD), to characterize genome-wide patterns of SNPs extracted from the HapMap data set, which includes data from 1184 healthy subjects of eleven populations. In addition, we have used cluster and classification analysis to relate the genetic distances within chromosomes based on FD similarities to the geographical distances among the 11 global populations. We found that HFD outperformed BCD at both grand average clusterization analysis by the cophenetic correlation coefficient, in which the closest value to 1 represents the most accurate clustering solution (0.981 for the HFD and 0.956 for the BCD) and classification (79.0% accuracy, 61.7% sensitivity, and 96.4% specificity for the HFD with respect to 69.1% accuracy, 43.2% sensitivity, and 94.9% specificity for the BCD) of the 11 populations present in the HapMap data set. These results support the evidence that HFD is a reliable measure helpful in representing individual variations within all chromosomes and categorizing individuals and global populations

Alzheimer's disease as a viral disease: Revisiting the infectious hypothesis

Alzheimer's disease (AD) represents the most frequent type of dementia in elderly people. Two major forms of the disease exist: sporadic-the causes of which have not yet been fully understood -and familial-inherited within families from generation to generation, with a clear autosomal dominant transmission of mutations in Presenilin 1 (PSEN1), 2 (PSEN2) or Amyloid Precursors Protein (APP) genes. The main hallmark of AD consists of extra -cellular deposits of amyloid-beta (A beta) peptide and intracellular deposits of the hyperphosphorylated form of the tau protein. An ever-growing body of research supports the viral infectious hypothesis of sporadic forms of AD. In particular, it has been shown that several herpes viruses (i.e., HHV-1, HHV-2, HHV-3 or varicella zoster virus, HHV-4 or Epstein Barr virus, HHV-5 or cytomegalovirus, HHV-6A and B, HHV-7), flaviviruses (i.e., Zika virus, Dengue fever virus, Japanese encephalitis virus) as well as Human Immunodeficiency Virus (HIV), hepatitis viruses (HAV, HBV, HCV, HDV, HEV), SARS-CoV2, Ljungan virus (LV), Influenza A virus and Borna disease virus, could increase the risk of AD. Here, we summarized and discussed these results. Based on these findings, sig-nificant issues for future studies are also put forward

An ELOVL2-Based Epigenetic Clock for Forensic Age Prediction: A Systematic Review

The prediction of chronological age from methylation-based biomarkers represents one of the most promising applications in the field of forensic sciences. Age-prediction models developed so far are not easily applicable for forensic caseworkers. Among the several attempts to pursue this objective, the formulation of single-locus models might represent a good strategy. The present work aimed to develop an accurate single-locus model for age prediction exploiting ELOVL2, a gene for which epigenetic alterations are most highly correlated with age. We carried out a systematic review of different published pyrosequencing datasets in which methylation of the ELOVL2 promoter was analysed to formulate age prediction models. Nine of these, with available datasets involving 2298 participants, were selected. We found that irrespective of which model was adopted, a very strong relationship between ELOVL2 methylation levels and age exists. In particular, the model giving the best age-prediction accuracy was the gradient boosting regressor with a prediction error of about 5.5 years. The findings reported here strongly support the use of ELOVL2 for the formulation of a single-locus epigenetic model, but the inclusion of additional, non-redundant markers is a fundamental requirement to apply a molecular model to forensic applications with more robust results

An ELOVL2-Based Epigenetic Clock for Forensic Age Prediction: A Systematic Review

The prediction of chronological age from methylation-based biomarkers represents one of the most promising applications in the field of forensic sciences. Age-prediction models developed so far are not easily applicable for forensic caseworkers. Among the several attempts to pursue this objective, the formulation of single-locus models might represent a good strategy. The present work aimed to develop an accurate single-locus model for age prediction exploiting ELOVL2, a gene for which epigenetic alterations are most highly correlated with age. We carried out a systematic review of different published pyrosequencing datasets in which methylation of the ELOVL2 promoter was analysed to formulate age prediction models. Nine of these, with available datasets involving 2298 participants, were selected. We found that irrespective of which model was adopted, a very strong relationship between ELOVL2 methylation levels and age exists. In particular, the model giving the best age-prediction accuracy was the gradient boosting regressor with a prediction error of about 5.5 years. The findings reported here strongly support the use of ELOVL2 for the formulation of a single-locus epigenetic model, but the inclusion of additional, non-redundant markers is a fundamental requirement to apply a molecular model to forensic applications with more robust results

A Blood-Based Molecular Clock for Biological Age Estimation

In the last decade, extensive efforts have been made to identify biomarkers of biological age. DNA methylation levels of ELOVL fatty acid elongase 2 (ELOVL2) and the signal joint T-cell receptor rearrangement excision circles (sjTRECs) represent the most promising candidates. Although these two non-redundant biomarkers echo important biological aspects of the ageing process in humans, a well-validated molecular clock exploiting these powerful candidates has not yet been formulated. The present study aimed to develop a more accurate molecular clock in a sample of 194 Italian individuals by re-analyzing the previously obtained EVOLV2 methylation data together with the amount of sjTRECs in the same blood samples. The proposed model showed a high prediction accuracy both in younger individuals with an error of about 2.5 years and in older subjects where a relatively low error was observed if compared with those reported in previously published studies. In conclusion, an easy, cost-effective and reliable model to measure the individual rate and the quality of aging in human population has been proposed. Further studies are required to validate the model and to extend its use in an applicative context

A Blood-Based Molecular Clock for Biological Age Estimation

In the last decade, extensive efforts have been made to identify biomarkers of biological age. DNA methylation levels of ELOVL fatty acid elongase 2 (ELOVL2) and the signal joint T-cell receptor rearrangement excision circles (sjTRECs) represent the most promising candidates. Although these two non-redundant biomarkers echo important biological aspects of the ageing process in humans, a well-validated molecular clock exploiting these powerful candidates has not yet been formulated. The present study aimed to develop a more accurate molecular clock in a sample of 194 Italian individuals by re-analyzing the previously obtained EVOLV2 methylation data together with the amount of sjTRECs in the same blood samples. The proposed model showed a high prediction accuracy both in younger individuals with an error of about 2.5 years and in older subjects where a relatively low error was observed if compared with those reported in previously published studies. In conclusion, an easy, cost-effective and reliable model to measure the individual rate and the quality of aging in human population has been proposed. Further studies are required to validate the model and to extend its use in an applicative context

ALS and CHARGE syndrome: a clinical and genetic study

Amyotrophic Lateral Sclerosis and CHARGE syndrome are complex neurological disorders, which never occurred together in the same family and, to date, no putative correlation between them has been described on PubMed Central. Due to our aim was to evaluate the presence of different genetic variants involved in these pathologies, we reported a clinical and genetic description of two sisters affected by these two different disorders. In the CHARGE patient, molecular analysis of the CHD7 gene revealed the c.8016G >A de novo variant in exon 37. The ALS patient had been screened negative for mutations in SOD1, TARDBP, FUS/TLS, C9orf72 and KIF5A genes. Anyway, targeted next generation sequencing analysis identified known and unknown genetic variations in 39 ALS-related genes: a total of 380 variants were reported, of which 194 in the ALS patient and 186 in the CHARGE patient. To date, although the results suggest that the occurrence of the two syndromes in the same family is co-incidental rather than based on a causative genetic variant, we could hypothesize that other factors might act as modulators in the pathogenesis of these different phenotypes

The Role of Mitochondrial Copy Number in Neurodegenerative Diseases: Present Insights and Future Directions

Neurodegenerative diseases are progressive disorders that affect the central nervous system (CNS) and represent the major cause of premature death in the elderly. One of the possible determinants of neurodegeneration is the change in mitochondrial function and content. Altered levels of mitochondrial DNA copy number (mtDNA-CN) in biological fluids have been reported during both the early stages and progression of the diseases. In patients affected by neurodegenerative diseases, changes in mtDNA-CN levels appear to correlate with mitochondrial dysfunction, cognitive decline, disease progression, and ultimately therapeutic interventions. In this review, we report the main results published up to April 2024, regarding the evaluation of mtDNA-CN levels in blood samples from patients affected by Alzheimer’s (AD), Parkinson’s (PD), and Huntington’s diseases (HD), amyotrophic lateral sclerosis (ALS), and multiple sclerosis (MS). The aim is to show a probable link between mtDNA-CN changes and neurodegenerative disorders. Understanding the causes underlying this association could provide useful information on the molecular mechanisms involved in neurodegeneration and offer the development of new diagnostic approaches and therapeutic interventions

Mutation Screening of Spastin, Atlastin, and REEP1 in Hereditary Spastic Paraplegia

Hereditary spastic paraplegia (HSP) comprises a group of clinically and genetically heterogeneous diseases that affect the upper motor neurons and their axonal projections. Over 40 chromosomal loci have been identified for autosomal dominant, recessive, and X-linked HSP. Mutations in the genes atlastin , spastin and REEP1 are estimated to account for up to 50% of autosomal dominant HSP and currently guide the molecular diagnosis of HSP. Here we report the mutation screening results of 120 HSP patients from North America for spastin, atlastin, and REEP1 , with the latter one partially reported previously. We identified mutations in 36.7% of all tested HSP patients and describe 20 novel changes in spastin and atlastin . Our results add to a growing number of HSP disease associated variants and confirm the high prevalence of atlastin , spastin , and REEP1 mutations in the HSP patient population

High-throughput sequencing of two populations of extracellular vesicles provides an mRNA signature that can be detected in the circulation of breast cancer patients

ABSTRACT Extracellular vesicles (EVs) contain a wide range of RNA types with a reported prevalence of non-coding RNA. To date a comprehensive characterization of the protein coding transcripts in EVs is still lacking. We performed RNA-Sequencing (RNA-Seq) of 2 EV populations and identified a small fraction of transcripts that were expressed at significantly different levels in large oncosomes and exosomes, suggesting they may mediate specialized functions. However, these 2 EV populations exhibited a common mRNA signature that, in comparison to their donor cells, was significantly enriched in mRNAs encoding E2F transcriptional targets and histone proteins. These mRNAs are primarily expressed in the S-phase of the cell cycle, suggesting that they may be packaged into EVs during S-phase. In silico analysis using subcellular compartment transcriptome data from the ENCODE cell line compendium revealed that EV mRNAs originate from a cytoplasmic RNA pool. The EV signature was independently identified in plasma of patients with breast cancer by RNA-Seq. Furthermore, several transcripts differentially expressed in EVs from patients versus controls mirrored differential expression between normal and breast cancer tissues. Altogether, this largest high-throughput profiling of EV mRNA demonstrates that EVs carry tumor-specific alterations and can be interrogated as a source of cancer-derived cargo